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SITIST 2015 Dev - Turning big data into presicion medicine real life examples

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SITIST 2015 Dev - Turning big data into presicion medicine real life examples

  1. 1. Turning Big Data into Presicion Medicine: Real Life Examples Ugur CANDAN – Chief Operating Officer SAP Turkey - @ugurcandan
  2. 2. © 2015 SAP SE or an SAP affiliate company. All rights reserved. 2 The Challenge: Big Data, inaccessible through format, organizational and legislative boundaries Diagnosis Tumor stage Pathol. Report Genomic markers RadiotherapyTissue sample Patient Timeline PubMed biomedical article database 23+ Mil. articles Clinical trials Currently more than 30,000 recruiting on ClinicalTrials.gov Cancer patient records 160,000 at NCT Heidelberg Clinical information management systems Often more than 50 GB Human proteome 160 Mil. data points (2.4 GB) per sample 3.7 TB raw proteome data on ProteomicsDB.org Prescription data 1.5 Bil. records from 10,000 doctors and 10 Mil. Patients (100 GB) Human genome/biological data 800 MB per full genome 15 PB+ in databases of leading institutes Medical imaging data Scan of a single organ in 1s creates 10GB of raw data
  3. 3. © 2015 SAP SE or an SAP affiliate company. All rights reserved. 3 SAP Industry Healthcare Solutions Unlocking the value with award winning offerings Prevention Precision Therapy Care Diagnosis, Decision Support & Monitoring Platform for Personalized Medicine • Enablement of Precision / Personalized Medicine • Analyze massive volumes of relevant data (e.g. patients, clinical, omics, third party) • Structured and unstructured information • SDKs/APIs for solutions and content from customers, partners, networks Health Engagement • Care Collaboration, with patients and consumers • Engage your care network • Motivate behavioral change • Prevention and risk detection Medical Insights • Patient cohorts and research • Genome analysis • Patient-trial matching • Analytics; e.g. Predictive SAP Patient Management (SAP’s Industry Solution Healthcare – ISH) • Patient Experience and Clinical Delivery • Drive operational excellence – from admission to bill
  4. 4. © 2015 SAP SE or an SAP affiliate company. All rights reserved. 4
  5. 5. 5© 2015 SAP SE or an SAP affiliate company. All rights reserved. 12,000 Çalışan 3,200 Bilim insanı 650,000 Hasta/yıl 1,4 B€ Gelir 600,000 Hasta Basına veri kaydı
  6. 6. © 2015 SAP SE or an SAP affiliate company. All rights reserved. 6Strictly Confidential Outlook – Enabling the Network GovernmentState Centers Physician Hospital Networks US Lab Instrument Vendor Life Sciences Hospital Networks Europe Global Content and Services Delivery  Trial Matching  Trial Analytics  Rare Cases Services Standardized Testing and Reports  Guidelines  Benchmarking  Decision Support Patient Payor
  7. 7. © 2015 SAP SE or an SAP affiliate company. All rights reserved. 7 Customer Use Case: ASCO CancerLinQ Links to more information: Video SAP Teams with ASCO to Fight Cancer / SAP News / The SAP Newsroom / The Spin news show / All this content is on the SAP page
  8. 8. © 2015 SAP SE or an SAP affiliate company. All rights reserved. 8 CancerLinQ Clinical User Portal With permission by ASCO/CLQ
  9. 9. © 2015 SAP SE or an SAP affiliate company. All rights reserved. 9 Customer Use Case: SAP Medical Research Insights at the Nationales Centrum für Tumorerkrankungen Heidelberg Prof. Dr. Christof von Kalle
  10. 10. © 2015 SAP SE or an SAP affiliate company. All rights reserved. Thank you

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